The authors gratefully acknowledge the support of the U.S. Office of Naval Research, ONR Undersea Signal Processing.
JASA Express Letters
Covariance matrices, Eigenvectors, Sonar arrays, Acoustic arrays, Acoustic signal processing
In sonar array processing, a challenging problem is the estimation of the data covariance matrix in the presence of moving targets in the water column, since the time interval of data local stationarity is limited. This work describes an eigenvector-based method for proper data segmentation into intervals that exhibit local stationarity, providing data-driven higher bounds for the number of snapshots available for computation of time-varying sample covariance matrices. Application of the test is illustrated with simulated data in a horizontal array for the detection of a quiet source in the presence of a loud interferer.
Quijano, J. E., & Zurk, L. M. (2014). An eigenvector-based test for local stationarity applied to array processing. Journal Of The Acoustical Society Of America, 135(6), EL277-EL283. doi:10.1121/1.4874224